vecdot

paddle. vecdot ( x: Tensor, y: Tensor, axis: int = - 1, name: str | None = None ) → Tensor [source]

Computes the dot product of two tensors along a specified axis.

This function multiplies two tensors element-wise and sums them along a specified axis to compute their dot product. It supports tensors of any dimensionality, including 0-D tensors, as long as the shapes of x and y are broadcastable along the specified axis.

Parameters

  • x (Tensor) – The first input tensor. It should be a tensor with dtype of float32, float64, int32, int64, complex64, or complex128.

  • y (Tensor) – The second input tensor. Its shape must be broadcastable with x along the specified axis, and it must have the same dtype as x.

  • axis (int, optional) – The axis along which to compute the dot product. Default is -1, which indicates the last axis.

  • name (str|None, optional) – Name of the output. Default is None. It’s used to print debug info for developers. Details: Name

Returns

A tensor containing the dot product of x and y along the specified axis.

Return type

Tensor

Examples

>>> import paddle
>>> x = paddle.to_tensor([[1, 2, 3], [4, 5, 6]], dtype='float32')
>>> y = paddle.to_tensor([[1, 2, 3], [4, 5, 6]], dtype='float32')
>>> result = paddle.linalg.vecdot(x, y, axis=1)
>>> print(result)
Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=True,
[14.0, 77.0])